Mining the Spectra

When Casey came up with the idea of using satellites to map glacier debris as part of her doctoral studies in Norway, colleagues and mentors told her it was a fool’s errand. Satellites had been used to map the geochemistry of particulates in arid environments, but nobody had tried to make such observations in icy environments.

She was told there would be more “noise” than signal; that the resolution of existing instruments wasn’t good enough; that it simply was not possible. “But I had worked with satellite data before,” she said, “and I knew how much untapped spectral information many sensors were collecting.”

Satellite instruments that detect light outside the range of human vision help scientists study the Earth’s surface. Conventional sensors may have a handful of bands, while hyperspectral instruments, like Hyperion, have hundreds. (Adapted from Casey et al, 2012.)

By “spectral information,” Casey is referring to information embedded in specific parts, or bands, of the electromagnetic spectrum. While the human eye perceives only a narrow portion of the spectrum, satellite instruments can sense a much broader range of wavelengths. Many sensors are tuned to be sensitive to types of energy—such as the infrared—that are invisible to human eyes.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument on Terra—built by Japan’s Ministry of Economy, Trade, and Industry—has six bands in the shortwave infrared (just beyond red light at 1.0 to 2.5 microns) and five in the thermal infrared (3 to 12 microns). The Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) on Landsats 7 and 8 also have bands in the shortwave and thermal infrared bands.

Near, shortwave, and thermal-infrared images of the Ngozumpa and Khumbu Glaciers. (NASA images by Robert Simmon, using ASTER data.)

These wavelengths are critical because each different type of particulate—be it ash, dust, or soot—leaves unique “spectral fingerprints” that satellite sensors can measure. By searching for the right clues in the right bands, Casey was able to get a glimpse into the geochemistry of the particles with a sensor that was hundreds of kilometers away.

Using spectral information from outside the range of visible light, Casey is able to map different types of debris, like granite-rich vs. schist-rich (top) or by silica content (lower). (Adapted from Casey et al, 2012., using ASTER data.)

By analyzing ASTER data from the visible to thermal infrared, for instance, she was able to discriminate between patches of dark red, iron-rich debris and lighter colored iron-poor debris on Switzerland’s Zmutt glacier. Looking at the tongue of Khumbu glacier in Nepal, she used ASTER to distinguish between dark, schist-rich debris and a lighter patch of granite-rich debris. Schist is a metamorphic rock, while granite is igneous.